Financial institutions offer customers a wide range of services related to banking, investments, loans and other financial services. While international banks may offer their customers more services than their regional counterparts, banks, in general, operate in a similar fashion regardless of their size. The various essential aspects, products, and lines of business of banks are often compartmentalized and separated into individual units, with each unit responsible for a unique function of the bank. For example, one unit may be responsible for processing applications, another may be responsible for processing deposits, and yet another may be responsible for claims and dispute resolutions. Other types of units may be responsible for the financial institution's credit card, insurance and investment related lines of business. By having requests and issues resolved by specialized units of experienced professionals trained in handling particular issues, cost-efficiency and effectiveness may be maximized.
However, as banks and their units grow, so does the complexity of incoming customer requests that may be received through any number of channels of any number of business units. Often the case, incoming requests contain multiple individualized requests, each of which must be processed and resolved by a particular unit. Moreover, individual requests often require the help and input of multiple units at the bank in order to fully resolve the issues. For example, in response to a notice from a customer that his account has not been fully credited with a check deposit, a unit responsible for check deposit claims may need to communicate with a debit account unit to get the customer account information; a reconcilement services unit to settle the differences with another bank; a retail claims deposit unit to resolve additional issues; and so on. Such inefficiencies may be partly attributed to the compartmentalization of customer information by the units, as each unit may store unique information about the customer and his or her accounts. This often leads to incomplete awareness of information among the business units and incomplete or incorrect responses to customer requests. The deficiencies of currently available systems become even more apparent as the customer requests become more complex.
With so many different units in a financial institution, the channels that are available to customers are numerous. Because customers are not well versed in the functional capabilities of every financial unit in a financial institution, the proper branch and channel for customers to submit requests are often unclear. The customers are left with difficult decisions, often resorting to blind guessing.
Furthermore, in order to fulfill customer service requests, users must have access to applications, services and data from all of the relevant sources. But, the resources necessary to fulfill such requests may vary greatly across an organization and from employee to employee. Employees, for instance, may have different responsibilities, capabilities, security clearances, and so on, each of which may dictate what resources should be accessible to each employee. Indeed, such entitlements may change from day-to-day based on business needs, entitlement requirements, regulations, and other factors. Ultimately, it is currently expensive, time-consuming and overly-burdensome to manage these entitlements on a manual basis and to reallocate employees while properly adjusting entitlements.
In addition, training is an essential tool to ensure that customer requests are being proficiently fulfilled. Indeed, employees must be adequately trained to properly utilize the applications, services and data that they would use when working with a customer. However, at present, access to such tools are not necessarily tied to the completion of any training, thereby allowing employees with little to no experience to have access to important customer data. Even where an employee is restricted from access to particular information until he or she completes training, the process of providing access to applications, information and other data based on this completion, is a manual and time-consuming process.
Accordingly, there is an essential need for a solution that can improve the experience of the customers and the efficiency of the financial institution in managing and processing customer service requests, including by dynamically providing the resources and information of the various units in a flexible, variable and portable manner as the requests are received over any number of channels. Further, the solution should reduce the complexities of service requests from the perspective of the customer, including by not requiring the customer to have integral knowledge of an institution's organizational structure when placing requests. Further still, the solution should dynamically manage entitlements and security while efficiently providing access to applications, services and data necessary for the processing of customer service requests.
Though tremendous efficiency may be gained through a system, further efficiencies may be gained by, for example, reducing systematic costs, removing unnecessary system operations, and streamlining customer interaction. Currently, there is no way of identifying where such improvements may be made.
To the extent that improvements can even be identified manually, the amount and complexity of data that is received and generated by embodiments of enterprise fulfillment systems is large and continues to grow at a tremendous rate. Such data may be stored at the enterprise fulfillment system as unstructured data, making it difficult to process and analyze the data in an efficient manner. For these reasons, it is currently difficult and extremely expensive to clearly identify the optimal solutions across all requests, workflows, and units of the financial institution.
Accordingly, the presently disclosed invention further improves upon embodiments of previously disclosed enterprise fulfillment systems by providing an analytics engine that dynamically gathers and analyzes service processing data, currently implemented workflow and business rules, and system performance data, in order to dynamically optimize performance of the enterprise fulfillment system.